Cluster Sampling Techniques in Quantal Response Teratology and Developmental Toxicity Studies
Gayle S. Bieler
and Rick L. Williams
1995, Biometrics
51, 764-776
Keywords:
clustered binary data; Taylor series variance, dose response;toxicology
Abstract
This paper
presents a model-free approach for evaluating teratology and
developmental toxicity data involving clustered binary responses. In
teratology studies, a major statistical problem arises from the
effect of intralitter correlation, or the potential for littermates
to respond similarly. Some statistical methods impose strict
distributional assumptions to account for extra-binomial variation,
while others rely on nonparametric resampling and empirical variance
estimation techniques. Quasi-likelihood methods and GEE's, which
model the marginal mean/variance relationship, also avoid strict
distributional assumptions. The proposed approach, often used to
analyze complex sample survey data, is based on a first-order Taylor
series approximation and a between- cluster variance estimation
procedure, yielding consistent variance estimates for binomial-based
proportions and regression coefficients from dose-response models.
The cluster sample technique, presented here in the context of a
logistic dose-response model, incorporates many of the advantages of quasi-likelihood
methods, are valid for any underlying correlation structure, and are
adaptable to a variety of analytical settings. The results of a
simulation study show the cluster sample technique to be a viable
competitor to other methods currently receiving attention.